Lessons
1A threshold is an operating decision35 min read
Calculate the cost and workload of two candidate thresholds.
- →Select a threshold from explicit error costs
- →Respect a finite review capacity
- →Compare candidate models under the same operating policy
2Ranking quality does not make scores trustworthy probabilities35 min read
Evaluate calibration with a concrete prediction group.
- →Check probability calibration separately from ranking
3A release needs an observable escape route35 min read
Specify a candidate rollout with a fallback and measurable stop conditions.
- →Design a rollout with measurable fallback conditions
4Drift is a symptom to investigate35 min read
Choose the next diagnostic check from a drift report.
- →Diagnose drift using features, labels, and service evidence
Skills in this course
- 01Select a threshold from explicit error costsSelect a threshold from explicit error costs.
- 02Check probability calibration separately from rankingCheck probability calibration separately from ranking.
- 03Design a rollout with measurable fallback conditionsDesign a rollout with measurable fallback conditions.
- 04Diagnose drift using features, labels, and service evidenceDiagnose drift using features, labels, and service evidence.
- 05Respect a finite review capacityRespect a finite review capacity.
- 06Compare candidate models under the same operating policyCompare candidate models under the same operating policy.